Radiomics based on MRI for preoperative prediction of the tumor budding grade in rectal cancer: a systematic review and meta-analysis
Fan Xu, Zhiguo Deng, Yongjian Li, Miaoxia Chen, Qing Huang, Hongzhen Wu, Yingying LiangBackground
Tumor budding (TB) is a critical histopathological feature of rectal cancer that is strongly associated with metastasis, recurrence, and poor prognosis.
Purpose
To evaluate the diagnostic performance of radiomics models based on magnetic resonance imaging (MRI) for preoperative prediction of TB grade in rectal cancer via systematic review and meta-analysis.
Material and Methods
A systematic search from PubMed, Cochrane Library, Web of Science, and Embase was conducted for original diagnostic studies up to 10 April 2026. Summary estimates of diagnostic accuracy were pooled using a random effects model. Threshold effect, subgroup, and meta-regression analyses were performed to explore the source of heterogeneity.
Results
Seven studies with a total of 1846 patients were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of MRI-based radiomics model were 0.82 (95% confidence interval [CI]=0.68–0.91), 0.80 (95% CI=0.65–0.89), 4.0 (95% CI=2.5–6.5), 0.22 (95% CI=0.13–0.39), and 18 (95% CI=10–32), respectively. The area under the summary receiver operating characteristic curve was 0.88 (95% CI=0.85–0.90). In subgroup analysis, multi-sequence MRI-based radiomics using T2-weighted (T2W) imaging, diffusion-weighted imaging (DWI) and contrast-enhanced T1-weighted (CE-T1W) imaging showed higher sensitivity compared with T2W imaging (87% vs. 67%;
Conclusion
MRI-based radiomics models show promising performance for predicting TB grade in rectal cancer, with multi-sequence models outperforming single-sequence approaches. However, due to the limited number of included studies and heterogeneity, further large-scale prospective studies are warranted to confirm these results.